{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. meta::\n",
    "   :description: A guide which introduces the most important steps to get started with pymoo, an open-source multi-objective optimization framework in Python."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    ".. meta::\n",
    "   :keywords: Multi-objective Optimization, Python, Evolutionary Computation, Optimization Test Problem, Hypervolume"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "raw_mimetype": "text/restructuredtext"
   },
   "source": [
    ".. _nb_getting_started:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting Started"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following we like to introduce *pymoo* by presenting an example optimization scenario. This guide goes through the most important steps to get started with our framework. First, we present an example optimization problem to be solved using *pymoo*. Second, we show how to formulate the optimization problem in our framework and how to instantiate an algorithm object to be used for optimization. Then, a termination criterion for the algorithm is defined and the optimization method is called. Finally, we quickly show a possible post-processing step which analyzes the optimization run performance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Multi-Objective Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In general, multi-objective optimization has several objective functions with subject to inequality and equality constraints to optimize <cite data-cite=\"multi_objective_book\"></cite>. The goal is to find a set of solutions that do not have any constraint violation and are as good as possible regarding all its objectives values. The problem definition in its general form is given by:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\begin{align}\n",
    "\\begin{split}\n",
    "\\min \\quad& f_{m}(x) \\quad \\quad \\quad \\quad m = 1,..,M  \\\\[4pt]\n",
    "\\text{s.t.}   \\quad& g_{j}(x) \\leq 0  \\quad \\; \\; \\,  \\quad j = 1,..,J \\\\[2pt]\n",
    "\\quad& h_{k}(x) = 0        \\quad  \\; \\; \\quad k = 1,..,K \\\\[4pt]\n",
    "\\quad& x_{i}^{L} \\leq x_{i} \\leq x_{i}^{U}  \\quad i = 1,..,N \\\\[2pt]\n",
    "\\end{split}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The formulation above defines a multi-objective optimization problem with $N$ variables, $M$ objectives, $J$ inequality and $K$ equality constraints. Moreover, for each variable $x_i$ lower and upper variable boundaries ($x_i^L$ and $x_i^U$) are defined."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example Optimization Problem\n",
    "\n",
    "In the following, we investigate exemplarily a bi-objective optimization with two constraints. \n",
    "The selection of a suitable optimization problem was made based on having enough complexity for the purpose of demonstration, but not being too difficult to lose track of the overall idea. Its definition is given by:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\begin{align} \n",
    "\\begin{split}\n",
    "\\min \\;\\; & f_1(x) = (x_1^2 + x_2^2) \\\\ \n",
    "\\max \\;\\; & f_2(x) = -(x_1-1)^2 - x_2^2 \\\\[1mm]\n",
    "\\text{s.t.} \\;\\; & g_1(x) = 2 \\, (x_1 - 0.1) \\, (x_1 - 0.9) \\leq 0\\\\ \n",
    "& g_2(x) = 20 \\, (x_1 - 0.4) \\, (x_1 - 0.6) \\geq 0\\\\[1mm] \n",
    "& -2 \\leq x_1 \\leq 2 \\\\\n",
    "& -2 \\leq x_2 \\leq 2\n",
    "\\end{split}\n",
    "\\end{align}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " It consists of two objectives ($M=2$) where $f_1(x)$ is minimized and $f_2(x)$ maximized. The optimization is with subject to two inequality constraints ($J=2$) where $g_1(x)$ is formulated as a less than and $g_2(x)$ as a greater than constraint. The problem is defined with respect to two variables ($N=2$), $x_1$ and $x_2$, which both are in the range $[-2,2]$. The problem does not contain any equality constraints ($K=0$). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "nbsphinx": "hidden"
   },
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 351,
       "width": 494
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "\n",
    "X1, X2 = np.meshgrid(np.linspace(-2, 2, 500), np.linspace(-2, 2, 500))\n",
    "\n",
    "F1 = X1**2 + X2**2\n",
    "F2 = (X1-1)**2 + X2**2\n",
    "G = X1**2 - X1 + 3/16\n",
    "\n",
    "G1 = 2 * (X1[0] - 0.1) * (X1[0] - 0.9)\n",
    "G2 = 20 * (X1[0] - 0.4) * (X1[0] - 0.6)\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('font', family='serif')\n",
    "\n",
    "levels = [0.02, 0.1, 0.25, 0.5, 0.8]\n",
    "plt.figure(figsize=(7, 5))\n",
    "CS = plt.contour(X1, X2, F1, levels, colors='black', alpha=0.5)\n",
    "CS.collections[0].set_label(\"$f_1(x)$\")\n",
    "\n",
    "CS = plt.contour(X1, X2, F2, levels, linestyles=\"dashed\", colors='black', alpha=0.5)\n",
    "CS.collections[0].set_label(\"$f_2(x)$\")\n",
    "\n",
    "plt.plot(X1[0], G1, linewidth=2.0, color=\"green\", linestyle='dotted')\n",
    "plt.plot(X1[0][G1<0], G1[G1<0], label=\"$g_1(x)$\", linewidth=2.0, color=\"green\")\n",
    "\n",
    "plt.plot(X1[0], G2, linewidth=2.0, color=\"blue\", linestyle='dotted')\n",
    "plt.plot(X1[0][X1[0]>0.6], G2[X1[0]>0.6], label=\"$g_2(x)$\",linewidth=2.0, color=\"blue\")\n",
    "plt.plot(X1[0][X1[0]<0.4], G2[X1[0]<0.4], linewidth=2.0, color=\"blue\")\n",
    "\n",
    "plt.plot(np.linspace(0.1,0.4,100), np.zeros(100),linewidth=3.0, color=\"orange\")\n",
    "plt.plot(np.linspace(0.6,0.9,100), np.zeros(100),linewidth=3.0, color=\"orange\")\n",
    "\n",
    "plt.xlim(-0.5, 1.5)\n",
    "plt.ylim(-0.5, 1)\n",
    "plt.xlabel(\"$x_1$\")\n",
    "plt.ylabel(\"$x_2$\")\n",
    "\n",
    "plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.12),\n",
    "          ncol=4, fancybox=True, shadow=False)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The figure above shows the contours of the problem. The contour lines of the objective function $f_1(x)$ is represented by a solid and $f_2(x)$ by a dashed line. The constraints $g_1(x)$ and $g_2(x)$ are parabolas which intersect the $x_1$-axis at $(0.1, 0.9)$ and $(0.4, 0.6)$. The pareto-optimal set is illustrated by a thick orange line. Through the combination of both constraints the pareto-set is split into two parts.\n",
    "Analytically, the pareto-optimal set is  given by $PS = \\{(x_1, x_2) \\,|\\, (0.1 \\leq x_1 \\leq 0.4) \\lor (0.6 \\leq x_1 \\leq 0.9) \\, \\land \\, x_2 = 0\\}$ and the Pareto-front by $f_2 = (\\sqrt{f_1} - 1)^2$ where $f_1$ is defined in $[0.01,0.16]$ and $[0.36,0.81]$.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Problem Definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In *pymoo*, we consider pure minimization problems for optimization in all our modules. However, without loss of generality an objective which is supposed to be maximized, can be multiplied by $-1$ and be minimized. Therefore, we minimize $-f_2(x)$ instead of maximizing $f_2(x)$ in our optimization problem. Furthermore, all constraint functions need to be formulated as a $\\leq 0$ constraint. \n",
    "The feasibility of a solution can, therefore, be expressed by:\n",
    "\n",
    "$$ \\begin{cases}\n",
    "\\text{feasible,} \\quad \\quad \\sum_i^n \\langle g_i(x)\\rangle = 0\\\\\n",
    "\\text{infeasbile,} \\quad \\quad \\quad \\text{otherwise}\\\\\n",
    "\\end{cases}\n",
    "$$\n",
    "\n",
    "$$\n",
    "\\text{where} \\quad \\langle g_i(x)\\rangle =\n",
    "\\begin{cases}\n",
    "0, \\quad \\quad \\; \\text{if} \\; g_i(x) \\leq 0\\\\\n",
    "g_i(x), \\quad  \\text{otherwise}\\\\\n",
    "\\end{cases}\n",
    "$$\n",
    "\n",
    "\n",
    "For this reason, $g_2(x)$ needs to be multiplied by $-1$ in order to flip the $\\geq$ to a $\\leq$ relation. We recommend the normalization of constraints to give equal importance to each of them. \n",
    "For $g_1(x)$, the coefficient results in $2 \\cdot (-0.1) \\cdot (-0.9) = 0.18$ and for $g_2(x)$ in $20 \\cdot (-0.4) \\cdot (-0.6) = 4.8$, respectively. We achieve normalization of constraints by dividing $g_1(x)$ and $g_2(x)$ by its corresponding coefficient.\n",
    "\n",
    "\n",
    "\n",
    "Finally, the optimization problem to be optimized using *pymoo* is defined by:\n",
    "\n",
    "\\begin{align} \n",
    "\\label{eq:getting_started_pymoo}\n",
    "\\begin{split}\n",
    "\\min \\;\\; & f_1(x) = (x_1^2 + x_2^2) \\\\ \n",
    "\\min \\;\\; & f_2(x) = (x_1-1)^2 + x_2^2 \\\\[1mm] \n",
    "\\text{s.t.} \\;\\; & g_1(x) = 2 \\, (x_1 - 0.1) \\, (x_1 - 0.9)  \\, /  \\,  0.18 \\leq 0\\\\ \n",
    "& g_2(x) = - 20 \\, (x_1 - 0.4) \\, (x_1 - 0.6) \\,  /  \\,  4.8 \\leq 0\\\\[1mm] \n",
    "& -2 \\leq x_1 \\leq 2 \\\\\n",
    "& -2 \\leq x_2 \\leq 2\n",
    "\\end{split}\n",
    "\\end{align}\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, the derived problem formulation is implemented in Python. Each optimization problem in *pymoo* has to inherit from the [Problem](problems/index.ipynb) class. First, by calling the `super()` function the problem properties such as the number of variables `n_var`, objectives `n_obj` and constraints `n_constr` are initialized. Furthermore, lower `xl` and upper variables boundaries `xu` are supplied as a NumPy array. Additionally, the evaluation function _evaluate needs to be overwritten from the superclass. \n",
    "The method takes a two-dimensional NumPy array x with n rows and m columns as an input. Each row represents an individual and each column an optimization variable. After doing the necessary calculations, the objective values have to be added to the dictionary out with the key `F` and the constraints with key `G`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from pymoo.util.misc import stack\n",
    "from pymoo.model.problem import Problem\n",
    "\n",
    "class MyProblem(Problem):\n",
    "\n",
    "    def __init__(self):\n",
    "        super().__init__(n_var=2, \n",
    "                         n_obj=2, \n",
    "                         n_constr=2, \n",
    "                         xl=np.array([-2,-2]), \n",
    "                         xu=np.array([2,2]))\n",
    "\n",
    "    def _evaluate(self, x, out, *args, **kwargs):\n",
    "        f1 = x[:,0]**2 + x[:,1]**2\n",
    "        f2 = (x[:,0]-1)**2 + x[:,1]**2\n",
    "        \n",
    "        g1 = 2*(x[:, 0]-0.1) * (x[:, 0]-0.9) / 0.18\n",
    "        g2 = - 20*(x[:, 0]-0.4) * (x[:, 0]-0.6) / 4.8\n",
    "        \n",
    "        out[\"F\"] = np.column_stack([f1, f2])\n",
    "        out[\"G\"] = np.column_stack([g1, g2])\n",
    "\n",
    "        \n",
    "    # --------------------------------------------------\n",
    "    # Pareto-front - not necessary but used for plotting\n",
    "    # --------------------------------------------------\n",
    "    def _calc_pareto_front(self, flatten=True, **kwargs):\n",
    "        f1_a = np.linspace(0.1**2, 0.4**2, 100)\n",
    "        f2_a = (np.sqrt(f1_a) - 1)**2\n",
    "        \n",
    "        f1_b = np.linspace(0.6**2, 0.9**2, 100)\n",
    "        f2_b = (np.sqrt(f1_b) - 1)**2\n",
    "        \n",
    "        a, b = np.column_stack([f1_a, f2_a]), np.column_stack([f1_b, f2_b])\n",
    "        return stack(a, b, flatten=flatten)\n",
    "    \n",
    "    # --------------------------------------------------\n",
    "    # Pareto-set - not necessary but used for plotting\n",
    "    # --------------------------------------------------\n",
    "    def _calc_pareto_set(self, flatten=True, **kwargs):\n",
    "        x1_a = np.linspace(0.1, 0.4, 50)\n",
    "        x1_b = np.linspace(0.6, 0.9, 50)\n",
    "        x2 = np.zeros(50)\n",
    "        \n",
    "        a, b = np.column_stack([x1_a, x2]), np.column_stack([x1_b, x2])\n",
    "        return stack(a,b, flatten=flatten)\n",
    "    \n",
    "problem = MyProblem()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because we consider a test problem where the optimal solutions in design and objective space are known, we have implemented the `_calc_pareto_front` and `_calc_pareto_set` functions to observe the convergence of the algorithm later on. For the optimization run itself the methods need not to be overwritten. **So, no worries if you are investigating benchmark or real-world optimization problems.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Moreover, we would like to mention that in many test optimization problems implementation already exist. For example, the test problem *ZDT1* can be initiated by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pymoo.factory import get_problem\n",
    "\n",
    "zdt1 = get_problem(\"zdt1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our framework has various single- and many-objective optimization test problems already implemented. Furthermore, a more advanced guide for custom problem definitions is available. In case problem functions are computationally expensive, parallelization of the evaluations functions might be an option.\n",
    "\n",
    "[Optimization Test Problems](problems/index.ipynb) | \n",
    "[Define a Custom Problem](problems/custom.ipynb) | \n",
    "[Parallelization](problems/parallelization.ipynb)\n",
    "[Callback](interface/callback.ipynb)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize an Algorithm\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Moreover, we need to initialize a method to optimize the problem.\n",
    "In *pymoo* factory methods create an `algorithm` object to be used for optimization. For each of those methods an API documentation is available and through supplying different parameters, algorithms can be customized in a plug-and-play manner.\n",
    "Depending on the optimization problem different algorithms can be used to optimize the problem. Our framework offers various [Algorithms](algorithms/index.ipynb) which can be used to solve problems with different characteristics."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In general, the choice of a suitable algorithm for optimization problems is a challenge itself. Whenever problem characteristics are known beforehand, we recommended using those through customized operators.\n",
    "However, in our case the optimization problem is rather simple, but the aspect of having two objectives and two constraints should be considered. For this reason, we decided to use [NSGA-II](algorithms/nsga2.ipynb) with its default configuration with minor modifications. We chose a population size of 40 (`pop_size=40`) and decided instead of generating the same number of offsprings to create only 10 (`n_offsprings=40`). This is a greedier  variant and improves the convergence of rather simple optimization problems without difficulties regarding optimization, such as the existence of local Pareto fronts.\n",
    "Moreover, we enable a duplicate check (`eliminate_duplicates=True`) which makes sure that the mating produces offsprings which are different with respect to themselves and the existing population regarding their design space values. To illustrate the customization aspect, we listed the other unmodified default operators in the code-snippet below. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pymoo.algorithms.nsga2 import NSGA2\n",
    "from pymoo.factory import get_sampling, get_crossover, get_mutation\n",
    "\n",
    "algorithm = NSGA2(\n",
    "    pop_size=40,\n",
    "    n_offsprings=10,\n",
    "    sampling=get_sampling(\"real_random\"),\n",
    "    crossover=get_crossover(\"real_sbx\", prob=0.9, eta=15),\n",
    "    mutation=get_mutation(\"real_pm\", eta=20),\n",
    "    eliminate_duplicates=True\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `algorithm` object contains the implementation of NSGA-II  with the custom settings supplied to the factory method."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define a Termination Criterion\n",
    "\n",
    "Furthermore, a termination criterion needs to be defined to finally start the optimization procedure. Different kind of [Termination Criteria](interface/termination.ipynb) are available. Here, since the problem is rather simple, we run the algorithm for some number of generations. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pymoo.factory import get_termination\n",
    "\n",
    "termination = get_termination(\"n_gen\", 40)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Instead of number of generations (or iterations) other criteria such as the number of function evaluations or the improvement in design or objective space from the last to the current generation can be used."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optimize"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we are solving the problem with the algorithm and termination criterion we have defined. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==========================================================================================\n",
      "n_gen |  n_eval |   cv (min)   |   cv (avg)   |     igd      |      gd      |      hv     \n",
      "==========================================================================================\n",
      "    1 |      40 |  0.00000E+00 |  2.36399E+01 |  0.355456661 |  0.005362269 |  0.259340233\n",
      "    2 |      50 |  0.00000E+00 |  1.15486E+01 |  0.355456661 |  0.005362269 |  0.259340233\n",
      "    3 |      60 |  0.00000E+00 |  5.277918607 |  0.355456661 |  0.005362269 |  0.259340233\n",
      "    4 |      70 |  0.00000E+00 |  2.406068542 |  0.336177786 |  0.003791374 |  0.267747228\n",
      "    5 |      80 |  0.00000E+00 |  0.908316880 |  0.146187673 |  0.030825699 |  0.326821728\n",
      "    6 |      90 |  0.00000E+00 |  0.264746300 |  0.146187673 |  0.030825699 |  0.326821728\n",
      "    7 |     100 |  0.00000E+00 |  0.054063822 |  0.127166639 |  0.048434536 |  0.326821728\n",
      "    8 |     110 |  0.00000E+00 |  0.003060876 |  0.116635438 |  0.040756917 |  0.333328216\n",
      "    9 |     120 |  0.00000E+00 |  0.00000E+00 |  0.085912985 |  0.018668919 |  0.342436730\n",
      "   10 |     130 |  0.00000E+00 |  0.00000E+00 |  0.077470550 |  0.033493862 |  0.355627493\n",
      "   11 |     140 |  0.00000E+00 |  0.00000E+00 |  0.077352198 |  0.040282741 |  0.356652764\n",
      "   12 |     150 |  0.00000E+00 |  0.00000E+00 |  0.053162450 |  0.004785549 |  0.392484461\n",
      "   13 |     160 |  0.00000E+00 |  0.00000E+00 |  0.044223026 |  0.004743970 |  0.407719675\n",
      "   14 |     170 |  0.00000E+00 |  0.00000E+00 |  0.038805143 |  0.005120891 |  0.410670860\n",
      "   15 |     180 |  0.00000E+00 |  0.00000E+00 |  0.037729492 |  0.004271793 |  0.412100954\n",
      "   16 |     190 |  0.00000E+00 |  0.00000E+00 |  0.036972091 |  0.007588808 |  0.414446121\n",
      "   17 |     200 |  0.00000E+00 |  0.00000E+00 |  0.034660980 |  0.006036578 |  0.419665136\n",
      "   18 |     210 |  0.00000E+00 |  0.00000E+00 |  0.033516235 |  0.005483394 |  0.420111173\n",
      "   19 |     220 |  0.00000E+00 |  0.00000E+00 |  0.024622717 |  0.005292631 |  0.427207379\n",
      "   20 |     230 |  0.00000E+00 |  0.00000E+00 |  0.023034030 |  0.004382377 |  0.440473619\n",
      "   21 |     240 |  0.00000E+00 |  0.00000E+00 |  0.016906921 |  0.004430595 |  0.452594419\n",
      "   22 |     250 |  0.00000E+00 |  0.00000E+00 |  0.016592436 |  0.004155185 |  0.453482517\n",
      "   23 |     260 |  0.00000E+00 |  0.00000E+00 |  0.016321930 |  0.004527221 |  0.453699792\n",
      "   24 |     270 |  0.00000E+00 |  0.00000E+00 |  0.013987946 |  0.004004738 |  0.455365890\n",
      "   25 |     280 |  0.00000E+00 |  0.00000E+00 |  0.013454690 |  0.004313685 |  0.455631510\n",
      "   26 |     290 |  0.00000E+00 |  0.00000E+00 |  0.012960456 |  0.004264848 |  0.455925267\n",
      "   27 |     300 |  0.00000E+00 |  0.00000E+00 |  0.012683256 |  0.004123014 |  0.456126518\n",
      "   28 |     310 |  0.00000E+00 |  0.00000E+00 |  0.012559351 |  0.004359358 |  0.456110146\n",
      "   29 |     320 |  0.00000E+00 |  0.00000E+00 |  0.012228516 |  0.003453151 |  0.456745602\n",
      "   30 |     330 |  0.00000E+00 |  0.00000E+00 |  0.011661748 |  0.003452586 |  0.457087950\n",
      "   31 |     340 |  0.00000E+00 |  0.00000E+00 |  0.011210955 |  0.003806385 |  0.457014270\n",
      "   32 |     350 |  0.00000E+00 |  0.00000E+00 |  0.010909137 |  0.003449675 |  0.457290422\n",
      "   33 |     360 |  0.00000E+00 |  0.00000E+00 |  0.010816517 |  0.003320362 |  0.457462656\n",
      "   34 |     370 |  0.00000E+00 |  0.00000E+00 |  0.010324079 |  0.003311767 |  0.457900371\n",
      "   35 |     380 |  0.00000E+00 |  0.00000E+00 |  0.010070886 |  0.003101986 |  0.458298915\n",
      "   36 |     390 |  0.00000E+00 |  0.00000E+00 |  0.009995280 |  0.003347647 |  0.458312542\n",
      "   37 |     400 |  0.00000E+00 |  0.00000E+00 |  0.009619601 |  0.003028411 |  0.458519325\n",
      "   38 |     410 |  0.00000E+00 |  0.00000E+00 |  0.009319637 |  0.002690949 |  0.458767148\n",
      "   39 |     420 |  0.00000E+00 |  0.00000E+00 |  0.009261538 |  0.002697147 |  0.458861977\n",
      "   40 |     430 |  0.00000E+00 |  0.00000E+00 |  0.009261263 |  0.002742830 |  0.458918287\n"
     ]
    }
   ],
   "source": [
    "from pymoo.optimize import minimize\n",
    "\n",
    "res = minimize(problem,\n",
    "               algorithm,\n",
    "               termination,\n",
    "               seed=1,\n",
    "               pf=problem.pareto_front(use_cache=False),\n",
    "               save_history=True,\n",
    "               verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The [Result](interface/result.ipynb) object provides the corresponding X and F values and some more information."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize\n",
    "\n",
    "The optimization results are illustrated below (design and objective space). The solid line represents the analytically derived Pareto set and front in the corresponding space and the circles solutions found by the algorithm. It can be observed that the algorithm was able to converge, and a set of nearly-optimal solutions was obtained. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 387,
       "width": 518
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 387,
       "width": 498
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pymoo.visualization.scatter import Scatter\n",
    "\n",
    "# get the pareto-set and pareto-front for plotting\n",
    "ps = problem.pareto_set(use_cache=False, flatten=False)\n",
    "pf = problem.pareto_front(use_cache=False, flatten=False)\n",
    "\n",
    "# Design Space\n",
    "plot = Scatter(title = \"Design Space\", axis_labels=\"x\")\n",
    "plot.add(res.X, s=30, facecolors='none', edgecolors='r')\n",
    "plot.add(ps, plot_type=\"line\", color=\"black\", alpha=0.7)\n",
    "plot.do()\n",
    "plot.apply(lambda ax: ax.set_xlim(-0.5, 1.5))\n",
    "plot.apply(lambda ax: ax.set_ylim(-2, 2))\n",
    "plot.show()\n",
    "\n",
    "# Objective Space\n",
    "plot = Scatter(title = \"Objective Space\")\n",
    "plot.add(res.F)\n",
    "plot.add(pf, plot_type=\"line\", color=\"black\", alpha=0.7)\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualization is an important post-processing step in multi-objective optimization. Although it seems to be pretty easy for our example optimization problem, it becomes much more difficult in higher dimensions where trade-offs between solutions are not easily observable. For visualizations in higher dimensions, various more advanced [Visualizations](visualization/index.ipynb) are implemented in our framework."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Performance Tracking\n",
    "\n",
    "If the optimization scenario is repetitive it makes sense to track the performance of the algorithm. Because we have stored the history of the optimization run, we can now analyze the convergence over time. To measure the performance, we need to decide what metric to be used. Here, we are using Hypervolume. Of course, other [Performance Indicators](misc/performance_indicator.ipynb) are available as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GXgUONbMD3X1HlG0DuPvkJP1aDExKV15ERESip2/SMy+fr4fwjpbt6EN8R8rPnr8sbbnY8tfOX6YAIiLrwuvQJOlDwmtjmno+SbDD0v0xwQMA7t5sZvcCpwMnArdF3LaIiIh0En2T/r5C/Sa9I+U72nZHH+JzLV/f2JzwzziVBcs3UN/YXJALq4stgFgaXquSpO8aly+Zti1c1yZJb7u/H+8HEFG1LSIiUtDy8U16R8vrm/TECvGb9I6U70jZF9e+k9ND/OwH6xkyoC+r39qcU/mDf/oQm1q2Z1WuTV1DkwKICDwEvAdMMzOL3U7VzIYRnCr9SgbbqK4PrzsnSd8lvMaud4iqbRERkbSKbTpMPr/F1zfp6evo6EP8z+9/mVFD+vP8mrdzeoj+xp+foXxAXza8uzWn8qf8/il2uOdUtvrb99La6hl/3ni/eHBZbgVDr23Ykj5TErkGHp2tqAKIcHrRDQRbsB4F3BuTfCbB9qvXtN0ws8EEIwjrgbNj1jP8kyA4ONjMdnb3tTFlyoBPhG/n59q2iIhILopxOkw+v8XvKd+kz36wnkljh7K9tZWX1+U2HebKe1+krLQ3r2/cknX5Jas2MuPqR7IqE+tPT6/OuSxA3Svr02dKYvuOHCOHAjCotDAf1S3uTLSCFy6AfgLYCTgJWEzwwH9LeP9od98e5v088Kew6FR3fzqmnv8GfgI8DZwPPEewC9P/Ehwa9wd3PzXXtnP8bIsnTZo0afHiZLu8iohId5buQRqgxMjpIT5V2bqGJk67YUFGD7QlBnNn1X7gm/Rcy0ZR/oTfPZnVw3BtVTl3fPkA6hubOeIX/8q4XJsfHbM3FYP6sbxpE1fd93LW5SeOGsz2Hc6L65qzLiv5sd+YnZg4agjL3mjmqVezC7wAzp2xO1N3Lefsmxalzxzn/ksO6bQpTJMnT2bJkiVLkm3uk0phhjUpuPvbZnYg8H3gdoLF0KuAnwI/iXuAf4JgR6X1wPNx9fzUzJYSbNv6d4JF0JuAZ4FZwI0dbFtERIpYV8/lL9bpMPn8Fj/Xhann37aYlevTbpqY0Lfvei6ncm2Wvv5Oh8rn0+D+vSnt3Ys3mt/LuuzMPUYwZddyFq/cwIMvvpF1+eMnj6ZXifHHRa9lXfZbn9yDs6dX8cqbmzjymseyLv/Tz+9LTWVZzkHnMfuPoqayjGlV5VkHu4W4/gGKMICA4EEeuDh8pcq3Btg9Rfp9wH2d0baIiORfMe3Ik6+H+Fwfwu9duoYdO8ip7I11y9llSH/W5DCVZsHyDZzw2ydwyDkI+Nuz69JnKkC9S4zSPr3YtqOV97a3Zl2+tqqcyeOG8sLad3jk5TezLn/JYTVMr67I6SH6m0ftET6Ej8gpgPjiIbsB5BRAzJgwgt69SpgwcnCHHuI7GgRcNHN8VqNtF84cn3E7Xa0oAwgREZFUim1Hnlwf4n/xQD3vbd+RU9npVz0EwMYtW9PkTuy8P/w7p3IA37/nhZzLAixc8VaHynfEbhUD2W34QNa+3cLza7IfTTjjgHH0KjHm1K3Iuuy3j96Ts6ZX5fxN+A8+t3f7N+m5BBBtAXg+H8I7+i1+Rx/iO1J+enUFVx47MeOphoV6BgRASb47ICIiEqU7Fq3itBsWJH3IaHuIvzPum8xspwHVNTR1uPz2Ha2sWr+ZW55Yke5jJTR7/jJ+++irOZV9feMWXt+4hXff25E+czdz1N4j+cYRE3Iq+9vTJnP9GVP5xYn75VT+lI+O46RpY3Mq2/ZA2fYQno1ED/G5lr9o5nhKLLNyyR7Ccy3f0bbbHuLT1ZHsIb6j5U+cOpa5s2qpTfL7r60qZ+6s2oRfUBQSjUCIiEi3UUw78sy6aRE73NlWpDvEVA7uR4kZa99uybrshMoyxpQPYNWGzdQ3Zr+Y+KSpY/jc/qNYv+k9vnpb9iMhlxxeQ01lGY8ue1PfpOfhm/SOlI/iW/wTp45l9NABXDt/GQsS/BnUVpVzYYqpih0tP726ov1wuY6ss8onBRAiItJt5BoEvJTjAVOfuvYx+vQuYVPLdpa9sSmr8i05zGGPN2nsEHr3Ksm67wBfPXR3Tpo6ltVvbeYLv1+Qdfm5s2oBcppK88uT9+/QotSzD6pqf9C6+cmVeZuT3pHyHW07nw/xkN+H8I62DR1/iI8iCKipLCuagCFe0W3j2p1pG1cRkdzl+jA6bGAfNmzeRr7+ORxR1o8RZf14Lof59PdfcgiQ20N87PaQuW6F2tGyUZTv6DawHdn+tqPlO9o2BJ+/Iw/SHS0P+Tt9PIq2e7IetY2riIhIIvFrEjK1/t1tEfckcxd8vJqvh3Pxc3mQLoTpMPn8Fh/0TXp3+Ca9I+WL+Vv8YqYAQkREuoVNLV1/FM8ZB47jM/vuwn1L13H948uzLl8+sG/7z8U6HSbfU2kg/3PSO1I+qvnw+XyIl55HAYSIiHQLg0pz+yft4sPGc9ieI/jUL+uyLntK7ThqKssoK+2TUwAR1YN4vh/C870oFfRNukhXUgAhIiLdQq57pn9y4s5539u+TTFPhymEqTSgB3GRrqAAQkREuoWayjLGlQ9g5YbMTyculB15YhX7dBhNpRHp/hRAiIhIt/CHBSuzCh4KaW/7RDQdRkQKlQIIEREpenc+/Rrfvuu5jPMX4o48IiLFQgGEiIgUtbv+vZpv/uXZ9vf7jt6Jr368mhseW150O/KIiBQDBRAiIlK0/vbsGr5+5zPth8DttfNgbjm7lp0G9OGIvUYW7Y48IiKFTAGEiIgUpX8+v46L/vif9vUGe4ws49ZzguChjR7iRUSipwBCREQKVrIRhIdeauT825awI4weqkcM4tZzaj9wMJuIiHQOBRAiIlJw6hqamD1/WcJzFSaMLOOVNzaxPQweqioGcts5tVQM6tfV3RQR6ZEUQIiISEG5Y9GqlFuhvryuuf3nseUDuO2LtYwYXNpFvRMRkZJ8d0BERKRNXUNT2nMUYn3t8PHsvFP/zu2UiIh8gAIIEREpGLPnL8s4eAC4feFrndcZERFJSAGEiIgUhPrG5oRrHlJZsHwD9Y3N6TOKiEhkFECIiEhBqGto6tJyIiKSGwUQIiJSEDa1bO/SciIikhsFECIiUhAGlea2MWCu5UREJDcKIEREpCBMr67o0nIiIpIbBRAiIlIQairLmLZreVZlaqvKqaks66QeiYhIIgogRESkYAwb1DfjvCUGF84c34m9ERGRRBRAiIhIQbj+sVe577l1GeUtMbjq2H00fUlEJA+08kxERPLunmfW8MO/v9j+fsq4IfQqKWFBgnMhaqvKuXDmeAUPIiJ5ogBCRETy6slX1vP1O59pfz9l3FBuPaeW0j69qG9spq6hiU0t2xlU2pvp1RVa8yAikmcKIEREJG9eWvcOX5r7NFt3tAKw+/CBXH/GFEr79AKChdUKGERECovWQIiISF6s2biFM+csojk8CG5EWT9uPnsaQwZkvpBaRES6ngIIERHpcm9v3saZNy5k3TstAAzq15ubzprG6KED8twzERFJR1OYRESkU8WvY5gybig/+PuL1DduAqBPL+N3p01mr10G57mnIiKSCQUQIiLSKeoampg9fxkLE+ykFOvq4/fVjkoiIkVEAYSIiETujkWruGzeUlo9db5P7j2Sz+43qms6JSIikdAaCBERiVRdQ1NGwQPAP55fR11DU+d3SkREIqMAQkREIjV7/rKMggeAVodr5y/r3A6JiEikFECIiEhk6hub0655iLdg+QbqG5s7qUciIhI1BRAiIhKZXKcjaRqTiEjxUAAhIiKR2RQeCtdV5UREpOspgBARkchsz3TxQ5xBpdoUUESkWOj/2CIi0mHbdrRy/WPL+c2jDTmV1zkQIiLFQwGEiEg3F38S9PTqCmoqyyIrv2TVW3xr3lJeWpfbQujaqvKs+iMiIvmlAEJEpJtKdRL0tKpyLpo5PuU3/+nKn3NwFY/VN3HrgpV4zMylseUDeO2tzR+4l0yJwYUzx2f0eUREpDAogBAR6YbSnQS9cPkGTrthAVcduw8nTB2TU/n4wKK0TwmXHFbD2QdVMW/J6rSHyZUYXHXsPpq+JCJSZBRAiIh0M5meBN3qcOm8Zxk1tP8HHuKzOUm6zYwJw/nBZ/dmTPkAAE6cOpbRQwdw7fxlLEgwglFbVc6FaUZARESkMCmAEBHpZnI5CTr2QT6b8gDVIwZx45lTMbMP3J9eXcH06ooOr8EQEZHCogBCRKQbyfUk6O/c/RwD+/Vm7dtbsi7f8MYmlr2xKWlQUFNZpoBBRKQbUQAhItKN5Hqi89ynVna4XQUJIiI9gw6SExHpRvJ1orNOkhYR6TmKcgTCzAYD3weOA0YAq4BbgJ+4+7YMys8AHs6gqbPc/aaYco8AH0uSd4e7F+XvU0QKX6brCDZv25FT/YeMr6B2t2E8u3oj/3y+MevyOklaRKTnKLr/44fBQx0wFDgJWAx8ApgLHGhmn3b3TP4F3Q68kiRtJ2Ak8FKCtNeAzUnqExGJVKZnOSxZ9Ra/fvgVHnwx+4d/gMs/tRc1lWXUNzbnFEBoNyURkZ6j6AII4EfA3sDR7v54eO8uM7sCuBr4MvDrDOp53d33SJRgZnOASe7+VILk0939key7LSKSnUzOYjj1hgXsOmwgy5vezbmd2JOgayrLmFZVntVCap0kLSLSsxTVGggzKwPOAdYC98Ul3wQ4cEkGVb0B3JOkjbaRjUyCEBGRTpHpWQzufCh4mDx2CHE7qiaV6CToi2aOp6QD5UVEpHsrthGIjwOlwAJ3/8A/q+6+3szqgQlmVuPu9ckqcfcXgAuSJJ8NbAX+EFGfRUSyPgsh27MYAI6dNIpzP7Y74yvL0o5eQPKToKdXV3DlsRN1krSIiCRUbAHExPC6Ikn6CmBCmC9pAJGMBacgfQW4xd2TzQc4zsyuAvYA+gDLgDuAX7h7S4btLE6SlHBKlYgUr0zXMMTK5SwHgK+EwQN0/CRonSQtIiLJFFsAMTK8vpUkfWN4rcyx/iOBauA3KfIcQjBN6gmgDDgTuBI4xswOTRF4iEgRy+U05UzWMJx2wwKuOnYfTpg6BoDtO1r548JVOfUx/iyGjp4ErZOkRUQkkWILIPqH12RbtW4NrwNyrP884GF3fzFJ+mXAC+7+dvi+BfiZmY0CLgJ+SAZrMNx9cqL74cjEpKx7LSKdJpcRhLZymaxhaHW4dN6zvLjuHdZs3MITr6ynOcczFZKdxdDRk6B1krSIiMQqqkXUwJbw2idJet/wmmib1ZTMbBxwNCkWT7v7kzHBQ6zrwutp4TQoEekG7li0itNuWJB0OlHbCMKdi177UFo2axhaHW6sW8E/n2/MOXgAncUgIiJdo9gCiHXhdWiS9CHhNZeN0L8S1n93DmVfJdgBahigCcEi3UC2Iwh1DU3t93Jdw9CmYlDf9JkS0HoEERHpCsX2ddXS8FqVJH3XuHwZMbN+wCzg1+6ey9d/Fr5EpIBlM5c/2xGEy+Y9y4wJI3j9rS0sfT3RQGV6n/hIJf915AR2Hz6IE697SmcxiIhIQSq2AOIh4D1gmplZ7FauZjYMqAFeSbWFaxLHE4xqXJcsg5mdCHzZ3T+eIHm38LoeaEqQLiJ5lO06hlxGEFZt2MItT67sUD8/sstOVI8IgoCLZo7ntBsWZBTE6CwGERHpSkU1hcndm4EbgJ2Bo+KSzyQYBbim7YaZDTazv5nZzWbWK0XV5wF/dfc1KfL0Bw40s9EJ0s4Nr7fFn08hIvmVyzqGR15+o6u69wGxaxjazmJId6CbzmIQEZGuVmwjEADfAmYA15nZScBi4BPA94D7gd/G5D2CYGE0wC+Bp+MrM7P9gAOAmWnadaAf8H9mdnHY7gCCg+e+AvwHuDyXDyQinSObdQzfDNcxvL5xC0tWJdspOrWP1QznpKlj2NHqnH/7v7MuHx8E6CwGEREpREUXQLj722Z2IPB94HZgBLAK+Cnwk7g1DE8QLHBeDzyfpMqvAi+7+0Npmr4trOcLBEHKWIIRj3rgu8A17p717k8i0nmyWcfgDn99JtUgZHozJgznqIk7A3DLUysjWcOgsxhERKTQFF0AAUEQAVwcvlLlWwPsnibPFzNscxvwt/AlIgWuozsh5cQtWd0AACAASURBVCJ2JCDqNQw6i0FERApFUa2BEBHJVOy2qtk4fvJonr78MKZVlWdVLn4EQWsYRESku1IAISLdUrJTmdMZWz6AikH9uGjm+LQP/22SjSCcOHUsc2fVUpskGKmtKmfurFpOmDomp76KiIjkQ1FOYRIRSSfXU5nbyrWNIKRbhJ1uBEFrGEREpLtRACEi3VKuU4Jiy0W5C5LWMIiISHehAEJEuqWayjImjR3CklUbMy6TaCckjSCIiIh8kAIIEemWdrQ6721vzTh/up2QNIIgIiIS0CJqEemW/veBl3l+zTsZ5dVOSCIiIpnTCISIdDsPvtDIrx5+pf39MfuPYs3GLTrNWUREJAIKIESkW1m5/l0uufM/7e8PqRnO1cfvS68S0zoGERGRCCiAEJFuo2XbDr5y6xKawzMgRg3pz+wT96NXeKCD1jGIiIh0nNZAiEi34O5cfvdzvLg2WPfQt1cJvz5lEkMH9s1zz0RERLoXBRAi0i38cdFr/Hnx6vb3V3xmL/YdMySPPRIREemeFECISNF7dvVGrvjr8+3vj5s0mpOnjc1jj0RERLovBRAiUtTeencr5966hK07gjMf9hhZxg8/tzdmlueeiYiIdE9aRC0iRSN+F6UDdhvGlfe9xOsbtwBQVtqb3546mf59e+W5pyIiIt2XAggRKXh1DU3Mnr+MhQnOcYj18+P3ZdeKgV3UKxERkZ5JAYSIFLQ7Fq3isnlLafXU+WZMGM4RHxnZNZ0SERHpwbQGQkQKVl1DU0bBA8C/6t+krqGp8zslIiLSwymAEJGCNXv+soyCB4BWh2vnL+vcDomIiIgCCBEpTPWNzWnXPMRbsHwD9Y3NndQjERERAQUQIlKgcp2OpGlMIiIinUsBhIgUpE0t27u0nIiIiGRGAYSIFKRBpbltEpdrOREREcmMAggRKUjTqyu6tJyIiIhkRgGEiBSkmsoyplWVZ1WmtqqcmsqyTuqRiIiIgAIIESlgF80cT4lllrfE4MKZ4zu3QyIiIqIAQkQK1/TqCq48diKWJogoMbjq2H00fUlERKQLKIAQkYJ24tSxfG6/UUnTa6vKmTurlhOmjunCXomIiPRc2q5ERArec6+/3f7z8ZNHM7Z8AINKezO9ukJrHkRERLqYAggRKWjLGptZ9sYmAPr36cX/fHZv+vftledeiYiI9FyawiQiBe3epevafz50j+EKHkRERPJMAYSIFLT7nlvb/vMnJ+6cx56IiIgIKIAQkQL2ypubeGldMwD9epdw6IQRee6RiIiIKIAQkYJ139L3Rx9mTBjOwH5atiUiIpJvCiBEpGDFrn/Q9CUREZHCoABCRArSiqZ3eWHtOwD07V3Cx/fQ9CUREZFCoABCRArSvTGLpw8ZP5yy0j557I2IiIi0UQAhIgXpvpjpS0fvMzKPPREREZFYCiBEpOCsWr+ZpeHp0317lTBzz8o890hERETaKIAQkYITe/bDweMrGKzpSyIiIgVDAYSIFJx7n3t/+tJR2n1JRESkoCiAEJGCsvqtzTzz2kYA+vQyDtf0JRERkYKiAEJECso/YkYfpldXsNMATV8SEREpJAogRKSg/D3m9OlP7q3pSyIiIoVGAYSIFIw1G7fw71XB9KVeJcbhe2n6koiISKFRACEiBSN2+tKBuw9j6MC+eeyNiIiIJKIAQkQKxr2x05e0+5KIiEhBUgAhIgVh3dstPL3yLSCYvnSEpi+JiIgUJAUQIlIQ/vn8+9OXPrpbOcMG9ctjb0RERCQZBRAiUhBid186SrsviYiIFKyiDCDMbLCZ/cLMVplZi5nVm9nlZpbRhvFmNsPMPIPXmQnK7mxmc8xsnZltMbNnzew8M7PIP6hID/FGcwuLVmwAoMTgyI+MzHOPREREJJne+e5AtsxsMFAHDAVOAhYDnwDmAgea2afdfUcGVW0HXkmSthMwEngpru3RwALgLeBIoAE4BfgVsB/wpWw/j4jAP59bh3vw87SqcoaXafqSiIhIoSq6AAL4EbA3cLS7Px7eu8vMrgCuBr4M/DqDel539z0SJZjZHGCSuz8Vl/QbYGfgSHd/Lrx3nZlNBM43s7vd/d4sP49Ij3fv0vfXP2j3JRERkcJWVFOYzKwMOAdYC9wXl3wT4MAlGVT1BnBPkjbaRjZ+HXd/PPApYGFM8NBmTnjNpG0RidG06T0WLF8PgBl8QtOXREREClpRBRDAx4FSYIF724SHgLuvB+qBajOrSVWJu7/g7hckST4b2Ar8Ie7+J8PrkwnKPANsBmaY2YDUH0FEYv3z+XW0hv81Tx1XzojBpfntkIiIiKRUbFOYJobXFUnSVwATwnz12VYeLoT+CnCLu7+badvu3mpmr4Vt70mwLiNVO8nSE06pEunO7ouZvnTURI0+iIiIFLpiG4Foe7p4K0n6xvCa6wlURwLVBGsdurptkR5nw7tbefLV9e3vtX2riIhI4Su2EYj+4XVbkvSt4TXXaUTnAQ+7+4ud2ba7T050PxyZmJSuvEh3cf/z69gRzl+aPG4oI3fS9CUREZFCV2wBxJbwmuy8h77hdXO2FZvZOOBo4MSublukp7r3uZjpS3tr+pKIiEgxKLYpTG1PG0OTpA8Jr4051P2VsP6789C2SI+zcfNWnmhoan9/lLZvFRERKQrFFkAsDa9VSdJ3jcuXETPrB8wCfu/u27Nt28xKgDHADiDR9CcRiXP/C41sD6cv7TdmCKOG9E9TQkRERApBsQUQDwHvAdPCHZPamdkwoAZ4xd2z3YHpeIKRhetS5Gk7IO6jCdL2JVj78Ii7awqTSAr1jc3cWLec3zzS0H7vaI0+iIiIFI1OWQNhZkOA44ApwAh3P87MqoGRMadHZ83dm83sBoLFzkfx/kM9wJmAAdfE9GMwcBuwHjjb3Xckqfo84K/uviZF28vM7F7gKDPbO+4wubPD6zUJiooIUNfQxOz5y1i4fMOH0v727Br22mUw06sr8tAzERERyUbkAYSZnQr8P6CM4IG+7cC30cBDZjbH3c/pQBPfAmYA15nZSQRnLnwC+B5wP/DbmLxHECyMBvgl8HSC/u4HHADMzKDtc4GngNvN7BSgATiVYP3EHHf/W/YfR6S41Dc2U9fQxKaW7Qwq7c306gpqKstSlrlj0Soum7e0/cC4eM+sfpvTbljAVcfuwwlTx3RCr0VERCQqkQYQZjYTuBlYCfwOWE34rby7P2JmU4F5Zna2u8/JpQ13f9vMDgS+D9wOjABWAT8FfhK3huEJ4FWCEYjnk1T5VeBld38og7ZXmdkU4EfAA8BOBEHEJcCvcvk8IsUi1QjCtKpyLpo5PuEIQl1DU8rgoU2rw6XznmXU0P4aiRARESlg5p7mX/VsKjO7n+Bh/kvu3hre2+HuvWLyfAq43N0TrSXo0cxs8aRJkyYtXpzyIGuRLpduBAGgxEg4gnDC755MGHQkU1tVzh1fPiDXroqIiEgGJk+ezJIlS5YkO58slagXUU8hCA5aU+R5BBgfcbsi0kmyHUGoi9matb6xOavgAWDB8g3UNzbn0lURERHpAlGvgSgF3kmTZyegX8TtikgnmT1/WdrgoU2rwzf+9AwHja9g/aatvLgut0CgrqEp7boKERERyY+oA4iXgbNIvR7gJHRWgkhRyGUEYc3bLdz59OoOtbupJdlxLCIiIpJvUQcQNwHXhAuNryc8fM3MegHjCLZa/QbBomMRKXCx05G60qDSTtlhWkRERCIQ9b/S/w/4OHAGcHrM/fcItnQFuItghyYRKXC5jgQctmclx08Zzeat27nkjmeyLq9dmERERApXpIuow4PaPgdcRDCdycJXCfACcD5wvEe59ZOIdJpcRwKmVw/jyI+M5Jj9RzOtqjyrsrVV5Vr/ICIiUsCi3oUJD/zS3fciOExuNDDI3Se6+28UPIgUj1xHAmLLXTRzPCWWInOMEoMLZ2qTNhERkUIWeQARy93fdfc17r459r6ZnZ6sjIgUjprKMkYN6Z9VmfgRhOnVFVx57MS0QUTbORKaviQiIlLYOjWASOHGPLUrIlm4bcEqXt+4JeP8yUYQTpw6lrmzaqlNMp2ptqqcubNqP3QInYiIiBSeyLc6MbNJwClADTCA9xdPi0gReeCFRi6/e2nG+dONIEyvrmB6dQX1jc3UNTSxqWU7g0p7M726QmseREREikikAYSZnQLcTPqRDa2DEClgi1e+xQW3L2k/QG7iqJ246LDx/P5fr7IgwbkQtVXlXDhzfEbTj2oqyxQwiIiIFLGoRyC+BzwIfBuod/eEx9CaWWvE7YpIRBre2MSsmxfRsi34z3TcsAHMOXMqw8v6cdielRpBEBER6eGiDiBGAYe4+9o0+W6OuF0RiUDjOy2cMWchGzdvA2DYwL7cfNY0hpf1a8+jEQQREZGeLepF1M9lmO+KiNsVkQ56p2UbZ8xZ2L5oun+fXsw5cyq7VgzMc89ERESkkEQ9AvEN4HIzu8DdU01TWg70irhtEclAoilI44YN4Mu3LOaldcGsw94lxm9OncS+Y4bkubciIiJSaCININz9UTNrAZ41s0XAWqAlyjZEJDd1DU3Mnr+MhQkWQZcP7MuGd7e2v7/quH2YMWFEV3ZPREREikTUuzBNBO4GKoG9UmTVLkwiXeiORau4bN7S9l2V4sUGD984cgKfnzy6i3omIiIixSbqKUzXAFuArwPLgES7MBkwP+J2RSSJuoamlMFDvH1H79S5HRIREZGiFnUAMQ2Y7u7PpspkZv+KuF0RSWL2/GUZBw8Av3yogYPGD++8DomIiEhRi3oXpg3AynSZ3P3QiNsVkQTqG5sTrnlIZcHyDdQ3JjzCRURERCTyAOJa4PR0mczs1YjbFZEE6hqaurSciIiIdH9RT2F6GvhvMzsY+DvJd2EaF3G7IpLAppbtXVpOREREur+oA4iHCXZYMuC4iOsWkSwNKs3tP/Fcy4mIiEj31xlPCf+TJt2A73RCuyISZ3p1RZeWExERke4v8gDC3b+fLo+ZfTfqdkXkw2oqy5hWVZ7VQuraqnJqKss6sVciIiJSzKJeRH1AhvmqIm5XRJK4aOZ4SiyzvCUGF84c37kdEhERkaIWaQDh7gsyzDosynZFJLnp1RV88eDd0uYrMbjq2H00fUlERERSytdKyUVArzy1LdKjuDsL0kxhqq0q58KZ4xU8iIiISFqRBhBa2yBSeP75/Dr+89pGAPr2KuH6M6bwypub2NSynUGlvZleXaE1DyIiIpKxqEcgvpcmvW2LV4+4XRFJYNuOVn76j5fb359+wDgOqRnOITXD89grERERKWadMYXp0AT3BgCjgGMI1l1c2QntikicO59+jVeb3gWgrLQ3Xz20Os89EhERkWIXdQDxvLs/miL9ejO7DNgP+FfEbYtIjM1bt3PNg8va3587Y3eGDuybxx6JiIhIdxD1LkwTM8h2HXBhlO2KyIfd8Nhy3mx+D4CRg0s560DtniwiIiIdF/U5EJkYCIzOQ7siPcb6Te/xu3+92v7+ksPH07+vNj4TERGRjuuyAMLM+pvZfsDvgVfT5ReR3P2/hxvY9N52AKpHDOK4SYrZRUREJBpRb+O6I8Osp0bZroi8b9X6zdz61Mr29/995AR698rHYKOIiIh0R1EvojYg0SJqB7YAy4Db3H1hxO2KSOjnD7zMth3BTslTxg3l8L0q89wjERER6U4i38bV3RNt4yoiXeC519/mr/9Z0/7+0qP2wMzy2CMRERHpbqKe13BWxPWJSBZ+8o+X2n8+fK9KpuxansfeiIiISHcU9TauN2eSz8y+G2W7IgKPLXuTx5Y1AVBi8M1PTMhzj0RERKQ7ytfKyivy1K5It9Ta6h8YfThhyhiqR5TlsUciIiLSXXVoDYSZPRRVR0Qkd/c8u4bnXn8HgNI+JVx8WE2eeyQiIiLdVUcXUc/IsZx3sF0RCW3d3srV97/c/v7s6VWM3Kk0jz0SERGR7qzDuzC5e9bToMystaPtivRk9Y3N1DU0sallO8+veZvXNmwBYMiAPnz5Y7vnuXciIiLSnXU0gEh05kNnlhPp0eoampg9fxkLl29ImH70xJ3ZqX+fLu6ViIiI9CQdCiByPfNBZ0WIZO+ORau4bN5SWlNMALx94Sr2HT2EE6aO6bqOiYiISI8S+UFyAGbWB/gsMBUYArwFLATucfdtndGmSHdW19CUNngAaHW4dN6zjBran+nVFV3TOREREelRIg8gzOwg4DZgFBB7BK4Dq83sZHevi7pdke5s9vxlaYOHNq0O185fpgBCREREOkWkAYSZ7QncRxAs3A28BLwLDAT2BA4H7jOzae7+UtKKRKRdfWNz0jUPySxYvoH6xmZqKnUWhIiIiEQr6hGI7wJLgGPc/UNPPGY2DJgHfAc4JeK2RbqluoamnMspgBAREZGoRX0S9QzgS4mCBwB3Xw98GZjZkUbMbLCZ/cLMVplZi5nVm9nl4dqLbOuabGa3m9nrZvaema0xs/lmdn6CvI+YmSd5be/IZxJJZlNLbn+1ci0nIiIikkrUAcRQ4NU0eV4hWFidEzMbDNQBxwMnh21+E7gU+KuZ9cqirlnAYwSjJpPDfp0CTAA+FECEXgNeTvDSlCzpFINKcxsozLWciIiISCpRP2GsAQ4k9TkPBwGrO9DGj4C9gaPd/fHw3l1mdgVwNcEIx6/TVWJmk4HrgEvc/dqYpIfN7L+A05MUPd3dH8m18yLZynUxtBZRi4iISGeIegTibmCumSWcomRmhwM3A3flUrmZlQHnAGsJFmvHuolg8fYlGVb3A2AT8Nv4BHf/o7t/Mpc+ikStprKMaVXlWZWprSrX+gcRERHpFFEHED8EtgH3m9kbZvaYmf0jvL4B/ANoIRhFyMXHgVJggbt/YFPLcH1FPVBtZjWpKgkXcx8BPOXuW3Psi0iXuWjmeEosfT6AEoMLZ47v3A6JiIhIjxVpABEunp4O/B8wLPz5iPBaTrAD00HuvjHHJiaG1xVJ0tvuT0yS3mYq0AtYZWafNLPHzexdM2sOg51jUpQ9zsyeMrONYZn/mNllZlaa8acQydL06grOOXi3tPlKDK46dh9NXxIREZFOE/kqS3dfBxxjZiMJFibvBGwEnnb3NzpY/cjw+laS9LbApDJNPbuH18OBY4EvAg8Cw4FfAvPM7L/c/ecJyh5CME3qCaAMOBO4kuAzH+ru76b7EGa2OEnSHunKSs+1cn3qv1q1VeVcOHO8ggcRERHpVFEfJPddd/8faA8k/h5l/UD/8LotSXrbdKQBaeoZHF7HAWe6+7zw/TtmdhLBIu+rzOzP7r4yptxlwAvu/nb4vgX4mZmNAi4imMKV6RoMkYy9tmEzD7zQ2P7+96dNZvXGLWxq2c6g0t5Mr67QmgcRERHpElGPQFxhZre5e0PE9bbZEl6TnffQN7xuzrA+B+78wA33d8zsHoItYo8FfhGT9mSSeq4jCCBOM7Ovxa/P+FCj7pMT3Q9HJiZl2HfpQW5+YgWt4d+qg8dXcPhHRqYuICIiItJJol5EbcC/w3UEZ5vZoIjrXxdehyZJbztfojFJepu2KVBN7r4lQXrbqEOmK1FfJQhGhgGaPyKReve97dzx9Gvt78+eXpXH3oiIiEhPF3UAAbALMJdgXcFaM7vJzA6OqO6l4TXZE9SucfmSeTG8pju5OuVIQgwLXyKR+8uS1TSHp0rvVjGQj9UMz3OPREREpCeLOoA4y92b3f06dz8AmEYwGnCHmTWY2eVmNqYD9T8EvAdMM7MPPLCHW7PWAK+4e32aehYAzcAQM0t0Kva48Np+urSZnWhmDyWpr217nPVAU5q2RTLW2urcVLei/f0ZB+5KSab7uYqIiIh0gqi3cb057v2L7v5NYAxwMcG6guVm9s8c628GbgB2Bo6KSz6TYBTgmrYbZjbYzP5mZjebWa+YelqA68O3p8ZWEh5W9ymC9RZ/iknqDxxoZqMTdO3c8HpbuvUPItl4tP5NXm0Kdl8q69eb4yYn+usnIiIi0nU6YwrTB4QjAxcQHB63R9jmlA5U+S3gBeA6MzvIzPqH5zZ8D7ifD54sfQRwNHA6sH9cPVcA/wF+YGafMbN+ZlYF3A4MBL4U7iTVxoF+wP+Z2SFmNtDMhpvZN4GvhHVd3oHPJfIhc+qWt/984tQxDOoX+c7LIiIiIlmJehvXHe7eK5xedBRwNsG3+X0IHsAfBG4kOFAuJ+7+tpkdCHyf4GF/BLAK+CnwE3ffHpP9CYIFzuuB5+PqaTazQ4BvE+y0NIZgWlMdcIi7PxHX9G1hPV8gCFLGEox41APfBa5x90x3fxJJq+GNZh5bFsyIK7Fg+pKIiIhIvkX9daaZ2Y8JvvHfmeAB+1XgZuAmd38tVeFMhecwXBy+UuVbw/uHxiVKbwYuDV/p2twG/C18iXS6G2PWPhy2ZyVjytMdbyIiIiLS+TpjPsSlBOcwzAVudPdHO6ENkW5t4+at/GXJ6vb3Z2nrVhERESkQnRFAnAPc6e6bOqFukR7hj4teo2VbKwB7jCzjo7uV57lHIiIiIoGoF1E/CjQA2ipGJEfbd7RyyxMr2t+ffVAVcbsWi4iIiORN1AHEx4CHSbM2QUSSu/+FRta83QLAsIF9+cy+u+S5RyIiIiLvi3oKkwPHuPv/RVyvSI8x5/H3t249uXYspX16pcgtIiIi0rWiHoFoAuZHXKdIj7F09ds8vfItAHqXGKd+dFyaEiIiIiJdK+oA4j7g0HSZzGxHxO2KdAs3xhwc96l9dqZycGkeeyMiIiLyYVFPYfoG8EczGwTMc/etSfJpRahInDeaW7jn2TXt77V1q4iIiBSiqAOIBUA/4A+Am9mbwJYE+TzidkWK3q1PrWLbjuA/jUljh7DvmCF57pGIiIjIh0UdQOwKrARWxdzTaINIGu9t38FtC1a2v9fog4iIiBSqyA+Sc/e0Tz5m1hp1uyLF7J5n1tK0KZjxt/NOpXxi75F57pGIiIhIYlEvov5dhvm+H3G7IkXL3T+wePq0A8bRp1fU/2mKiIiIRCPSpxR3PzfDfAogREILl2/g+TXvAFDap4QvTB2b5x6JiIiIJBf5FCYAMzPg48AUoNLdv2ZmuwB93H1l6tIi3V99YzN1DU1satnO35eubb9/zP6jGDqwbx57JiIiIpJa5AGEmR0KzAHGEiygduBrwN7AvWb2PXf/YdTtihSDuoYmZs9fxsLlGxKm76edl0RERKTARRpAmNkk4F5gG/BnYDVwcZj8AHAicL2ZveDu86JsWyRbsaMAg0p7M726gprKsk4rf8eiVVw2bymtKTYxvmzeUgzjhKljsvkoIiIiIl0m6hGI7wAPAqe4+zsAZnYxgLs78Bcz6wdcACiAkLxINQowraqci2aOZ3p1RaTl6xqa0gYPAK0Ol857llFD+6fsg4iIiEi+RL3Vy3TggrbgIYl7gb0iblckI3csWsVpNyxIOoVo4fINnHbDAu5c9Fqk5WfPX5Y2eGjT6nDt/GWZZRYRERHpYlEHEIOBNWny9AUynyciEpFsRwHqGpoiKV/f2Jw04EhmwfIN1Dc2Z1VGREREpCtEPYVpOfA54M4UeY4GXom4XZG0chkFiJ1GlG35i//4b6pHlPHC2lQDcsnVNTRltSZDREREpCtEHUD8EZhjZnsC17v7620JZtYHOA34X+AnEbcrklKuowCf/80TDOzXm3ff287TK9/Kqvybm7by5qb1WZWJtalle85lRURERDpL1AHET4FPAlcA3zWztwDMbBWwM8GUqaeAn0fcrkhK8dORMpVt0BClQaWdckyLiIiISIdEfRL1FmAG8AtgE1BOcBbE6PD91cBMd98aZbsi6eTr2/xj9h/F9adPyamsdmESERGRQhT1ImrcfYu7f50geJgIHERwiNwwd/+mu7dE3aZIOrl+m39y7VhuPGsqJ9eOzan8PqN34rC9KplWVZ5Vudqqcq1/EBERkYIUeQDRxt13uPvz7v6Eu7/g7q2d1ZZIOrl+m3/mgbty6IQRnHngrh1q96KZ4ymxzMqUGFw4c3xO7YmIiIh0tk4JIMxsFzP7mpndYmZ/Da+XmNnOndGeSDo1lWUdGgXoaPnp1RVceezEtEFEicFVx+6j6UsiIiJSsCIPIMzsIoJtWn8GnAp8OrxeDbxiZudH3aZIJjo6CtDR8idOHcvcWbXUJglEaqvKmTurlhOmjsmsEREREZE8iHSbFzM7lWAB9RrgbuBl4F1gILAHwRkRs81svbvfHmXbIum0jQKkOwwu2ShAR8u31TG9uoL6xmbqGprY1LKdQaW9mV5doTUPIiIiUhSi3ifyv4A/A6cm2mnJzC4B/gB8E1AAIV3uxKljGT10AFfd9xJLX3/7Q+m1VeVcOHN80ilEbeWvnb+MBQnOlUhXvk1NZZkCBhERESlKUQcQE4Cjk23T6u5bwyBiWcTtimRsenUFXz+ihjNvXATAmPL+nD29KuNRAI0iiIiISE8WdQDxNpDu6N0mIH+nc4kAb7zzXvvPU8aVc9b0qqzr0CiCiIiI9ERRL6K+H/hsmjyfA/4Se8PMHoq4HyIpNb7z/nEklYNL89gTERERkeIS9QjEN4F7zGwCcCewyt03m9kAYCxwErA/cHJcuY9F3A+RlBqbYwOIfnnsiYiIiEhxiTqAWB1e9weuADBLuO/lO0nui3SJxpgpTBqBEBEREclc1AGEAY/mUObgiPshktIHpzBpBEJEREQkU1EHELj7odmWMbPWqPshkkpsADGiTCMQIiIiIpmKehH197u4nEjWdrQ6bza/P4VphEYgRERERDIWdQCR02Jod1cAIV1m/ab32k+SLh/Yl369e+W3QyIiIiJFJOoAYoaZnRXuuiRSkGIXUI8o0+iDiIiISDaiDiAAvgSsMbNfm9m+nVC/SIfoDAgRERGR3EUeQLj7AQS7Ku0AHjazhWY2S6MSUijWaQcmERERkZxFHUBUdm2kQQAAIABJREFUAbj7Une/ANgF+DVwNrDWzH5jZpMiblMkK29oBEJEREQkZ5EGEO6+Mu59i7vf5O7TgQuBM4BFZva0mX3RzAZG2b5IJnSInIiIiEjuIg0gzOyQuPcDwulLC4E5QCnQBNQBJxOslbjKzPQUJ12msVkjECIiIiK5ivoguYeBXuHi6S8TBAllMWnXAXe5+zYAM6sBfgbcCHwh4r6IJPTBEQitgRARERH5/+3de7xcVXnw8d+TEHIhCSGEAAoSUC4qFwFBBLUoIipqX8WqVaARFbVSKUprsSLBllbB1jsoFgzqq6gtouKlKogXwIAogtxCuAivkMQECCchV/K8f+x9yGQyc86cOTNnzsz5fT+f/dmevfbae+01CzPP7HUZilYHEBERvwYOAQJYCnwe+GJm3l19cmYujIjjgT+1uBxSXc7CJEmS1LxWBxBQBA9XUrxtuDwzN9Q7MSImUrx5iDaUQ9rC2g1P8PCqdQCMC9h+m607XCJJkqTu0o4A4hmZeW+D5+4PvAP4dhvKIW3hz32bui/tMG0iW41vx1IokiRJvWtY354i4sSqQ2c3Ejz058vMGzLzkMysvo7UFs7AJEmSNDzD/fn1S5V/ZObZzeSTRkrlGhCzpxlASJIkDdVwuzBFRJzJCI9hiIjpwNnAccBs4H7gy8DH+md4GsK1DgZOB14EzAKWA7dTzBb12Rrn7wycA7wS2Ba4i2Kg+AWZmc0+k0aGq1BLkiQNTyvGQMxjywAiaxyrPN70F+0yeLgG2A54E3Aj8HLgK8DhEfHqzHyiwWu9DfgMcBZwGrACOKy81inAZ6vO3wVYADwCHAMsAt4CfA54DnBys8+lkWEXJkmSpOFpRQDxkaq/A/gwxRuCWgI4cxj3OwfYFzg2M39VHvt2RJwFfJxi/YnzB7tI+ebhQuC0zPx0RdLPIuJ0oNa4jAuAnYFjMvMP5bELI2I/4JSIuDwzf9DUU2lEVHZh2skAQpIkaciGHUDUGvcQEWcONB4iIj7czL0iYhrwduAh4IdVyfMpFqU7jQYCCOBfgJUU3Y82k5mXApdW3XtP4FXAgorgod/FFG8sTgMMIEaxylWoZ9uFSZIkaciGO4j6rSOc7yXAJIov8Zt1g8rM5cBC4BnlCtd1RcT2wMuAX2fmugbv/cpyf12NtN8DjwNHRsSUBq+nDrALkyRJ0vAMK4DIzEtGMh+wX7m/r056//H96qT3OwQYD9wfEa+MiF9FxKqI6IuIX0bEa4dy78zcCDxA8UbnmYPcWx3kKtSSJEnD046F5Nppp3L/SJ30R8v9joNc5+nl/mjgdRSL2f0U2IFiUPVlEXF6Zv5HG+5NRNxYJ2mfwfKqeY+v20DfmmJh9Anjg+2mTOhwiSRJkrpPty3DO7nc15uqtb870mDdiKaX+92A92XmZZn5WGbeTTGzUx/w0YjYrQ33VodUdl+aPW0SESM6+7AkSVJPGO5K1PeMZD5gdbmv99Px1uX+8Qavl8A3NzuQ+RjwPYq3M69rx70z8+BaG3BHg+VWEyq7L+20rd2XJEmSmjHcNxBzRjjf4nK/XZ30GeV+ySDX6e+GtCwzV9dI/2O537MN91aHLHEROUmSpGEb9hiIiKi5aFu946VmF5K7pdzvXid9TtV59dxe7gfrBF9Zzrr3johxwK7AExXX1iiztKoLkyRJkoauFWMgoomtWVcBa4FDo6oDezk1617A3Zm5cJDrLKAY5zAjImbUSO8f+1DZpah/fYfDapx/AMXYh6szs9HuUxphi52BSZIkadiGG0BkZo4b6jaMm/UBF1GsBv2KquS5FMHJJ/sPRMT0iLgiIi6JiPEV11kD/Ff55/GVFykXq3sVxZiHb1XkuYsiiDg0IvatuvdJ5f6TaNSyC5MkSdLwDTeAuH+E8wF8ELgNuDAiXhARk8t1G+YBP2bzlaVfBhwLnAgcWHWds4CbgH+JiNdExMSI2B34OrANcHJmLq7K826KsRBfj4j9I2JKRJwMvAu4ODOvGMZzqc0quzDt5BsISZKkpgxrDERm1huL0JZ8Zd4VEXE4cDbFl/3ZFAHJucDHMnNDxenXAvcAy4Fbq67TFxEvAv4Z+ATFGIY+4BrgRZl5bY173x8RzwXOAX4CbAssAk4DPtfsM2lkLOnb9AZitgGEJElSU7ptITmgCCKAvy+3gc57kE2LxtVK7wP+qdwavfeDwFsbPV+jQ2bahUmSJKkFum0hOakpj63ZwJr1GwGYsvV4pk7sythZkiSp4wwgNCYsqZqByVWoJUmSmmMAoTHB7kuSJEmtYQChMWFJxQxMrgEhSZLUPAMIjQnVXZgkSZLUHAMIjQlLKwKI2dPswiRJktQsAwiNCYt9AyFJktQSBhAaEyrHQOy0rQGEJElSswwgNCZUdmHacZoBhCRJUrMMINTzNm5MlvZtegMx22lcJUmSmmYAoZ738OPr2LAxAdh28gQmTRjf4RJJkiR1LwMI9bzFK1xETpIkqVUMINTzlvY5A5MkSVKrGECo57kKtSRJUusYQKjnbb4KtV2YJEmShsMAQj3PNxCSJEmtYwChnle5BsRs14CQJEkaFgMI9bzFdmGSJElqGQMI9bzKLkw7besbCEmSpOEwgFBPW//ERpavKgKICJg11TcQkiRJw2EAoZ62bOVasliEmu23mciE8TZ5SZKk4fDblHra5jMw+fZBkiRpuAwg1NMWr3AVakmSpFYygFBPW9pnACFJktRKBhDqaa5CLUmS1FoGEOpprkItSZLUWgYQ6mm+gZAkSWotAwj1tKUVbyBmT/MNhCRJ0nAZQKinLa54A+Eq1JIkScNnAKGetWb9E6xYvR6ArcYFM6ds3eESSZIkdT8DCPWszbsvTWTcuOhgaSRJknqDAYR61pKKNSBmOwOTJElSSxhAqGc5A5MkSVLrGUCoZy1e4SrUkiRJrWYAoZ61tM9F5CRJklrNAEI9a/MuTAYQkiRJrWAAoZ7lGAhJkqTWM4BQz6qcxtU3EJIkSa1hAKGelJmbrUK94zQDCEmSpFYwgFBPWrl2A4+vewKASRPGMX3yVh0ukSRJUm8wgFBPWlLVfSnCVaglSZJawQBCPWmp3ZckSZLawgBCPWlJ36YAYrYzMEmSJLWMAYR6UnUXJkmSJLWGAYR60uIVm95A7GQAIUmS1DIGEOpJS+3CJEmS1BYGEOpJdmGSJElqDwMI9aQllbMwGUBIkiS1jAGEek5msrTiDcTsaXZhkiRJahUDCPWcRx5fz7onNgIwbeJWbDPRVaglSZJapSsDiIiYHhGfiIj7I2JNRCyMiA9FxIQhXGNeROQA2wtq5Ll6gPM3tPYp1azNui9ta/clSZKkVuq6n2YjYjpwDbAd8CbgRuDlwFeAwyPi1Zn5RIOXWw4sq5P2eJ3jD9RJM4AYJTYf/2D3JUmSpFbqugACOAfYFzg2M39VHvt2RJwFfBx4J3B+g9f6bGbOG+L9T8zMq4eYRyOocvzDjtN8AyFJktRKXdWFKSKmAW8HHgJ+WJU8H0jgtBEulkaZyjcQs52BSZIkqaW6KoAAXgJMAhZkZlYmZOZyYCHwjIjYqxOF0+iw2C5MkiRJbdNtAcR+5f6+Oun9x/erk17tORFxRUQsjoi1EXF3RHw2Ip46QJ7jIuLXEfFoRKyKiJsi4oyI8KfuUaJyEbmdfAMhSZLUUt02BmKncv9InfRHy/2ODV7vBcD7geOB9cAxwOeBN0bEX2TmbTXyvIiim9S1wDRgLvDvwGsj4sWZuWqwm0bEjXWS9mmw3BrA0j67MEmSJLVLtwUQk8v9+jrp68r9lAau9TXgy5l5T8WxyyJiI/Bt4KvAQVV5zgBuy8wV5d9rgPPKNxanAv+KYzA6zlmYJEmS2qfbujCtLvf11nvYutzXm4L1SZm5sCp46PcdYAlwYETsV5XnuorgodKF5f6EiIgG7n1wrQ24Y7C8GtgTG5M/923qwrSDq1BLkiS1VLcFEIvL/XZ10meU+yXN3qAcnH1v+WejXYruoZgBantgVrP31vAtX7mWjeXw+pnbbM3ErcZ3tkCSJEk9ptsCiFvK/e510udUndesQd8i1Dh/qHnUBpvPwOT4B0mSpFbrtgDiKmAtcGh1V6GI2B7YC7g7MxcOdJGI2LWceWlGjbQA9ij/vLPi+Bsj4qo6l+w/f6CVrTUCKmdgcvyDJElS63VVAJGZfcBFwM7AK6qS51K8Bfhk/4GImF5O03pJRFT2ZRlPMVPT0TVucxywA3Azm7/JmAwcHhG71Mjz7nL/ter1KTSyNhtA7SrUkiRJLddVAUTpg8BtwIUR8YKImBwRrwXmAT+mmIa138uAY4ETgQMrjvd/yf9cRLw5ImZFxDYRcRxwAcU0sSdWBQMJTAS+GxEvKs/fISI+ALwLuAn4UMufVkOy1BmYJEmS2qrbpnElM1dExOHA2cDXgdnA/cC5wMcyc0PF6ddSDHBeDtxacY0/RsShwFuA04HPAFOBB4BvAh/NzAeqbv218jp/TRGkPI3ijcdC4MPAJzNz0Nmf1F6VXZhcA0KSJKn1ui6AgCKIAP6+3AY670Hg6XXSbgBuGMI91wNXlJtGqcpB1K5CLUmS1Hrd2IVJqmuJszBJkiS1lQGEesrSPmdhkiRJaicDCPWMtRue4OFV6wAYF7D9VAMISZKkVjOAUM/4c8Xbhx2mTWT8ONf2kyRJajUDCPWMzReRc/yDJElSOxhAqGc4gFqSJKn9DCDUM5a4iJwkSVLbGUCoZ2zWhWmabyAkSZLawQBCPWOpXZgkSZLazgBCPWNJ36YAYrZdmCRJktrCAEI9Y/GKTQHETtv6BkKSJKkdDCDUM5Y6BkKSJKntDCDUE1at3UDf2g0AbD1+HDOmTOhwiSRJknqTAYR6wtKKVahnT59IhKtQS5IktYMBhHqCi8hJkiSNDAMI9YTKAGInAwhJkqS2MYBQT6gMIJzCVZIkqX0MINQTNluF2jcQkiRJbWMAoZ6w+RgI30BIkiS1iwGEeoJrQEiSJI0MAwj1hCV9FW8gXIVakiSpbQwg1PUyk8UrnMZVkiRpJBhAqOs9tnoDazdsBGCbrcczdeJWHS6RJElS7zKAUNfbrPuSbx8kSZLaygBCXc81ICRJkkaOAYS6nmtASJIkjRwDCHW9yjcQOxlASJIktZUBhLre5l2YDCAkSZLayQBCXc9VqCVJkkaOAYS6nmMgJEmSRo4BhLre0so3ENMMICRJktrJAEJdbePGZGnfpjcQTuMqSZLUXgYQ6mrLV61jw8YEYMaUCUyaML7DJZIkSeptBhDqakvsviRJkjSiDCDU1Zb2uQq1JEnSSDKAUNdauKSPy377pyf/tvuSJElS+23V6QJIQ3XNomV86sq7uP7ehzc7/pPblvCGL1zHqUftyRHPmNWh0kmSJPU230Coq3zjhvs54aIFWwQP/a6/92FOuGgB37zhgREumSRJ0thgAKGucc2iZZxx2S2Uky7VtTHhny67mWsWLRuZgkmSJI0hBhDqGp+68q5Bg4d+GxM+feVd7S2QJEnSGGQAoa6wcElf3W5L9Sy492EWLulrU4kkSZLGJgMIdYVmuyPZjUmSJKm1DCDUFVau2TCi+SRJklSbAYS6wtRJzc043Gw+SZIk1WYAoa7Q7LoOrgchSZLUWgYQ6gp77TiNQ3efOaQ8z9t9JnvtOK1NJZIkSRqbDCDUNY54+vYNnzsu4L1H7dnG0kiSJI1NBhDqCjf+8WHOv/ruhs4dF/DR1+1v9yVJkqQ2cISpRr1FS1fytkt+w9oNGwGYPX0iu8yYzG/vf3SLc5+3+0zee9SeBg+SJEltYgChUW3JY2v4m4uv59HH1wOw/TZb882Tn8+cWduwcEkf1yxaxso1G5g6aSuOeMYsxzxIkiS1WVcGEBExHTgbOA6YDdwPfBn4WGaub/Aa84CzBjjlhZn5qxr5dgbOAV4JbAvcBXweuCAzcwiPoUE8tmY9c790A396dDUAkyeM5+K5hzBn1jZAMbDagEGSJGlkdV0AUQYP1wDbAW8CbgReDnwFODwiXp2ZTzR4ueVAvaWKH69x712ABcAjwDHAIuAtwOeA5wAnN/4kGsjaDU/wrq/cyO0PPQbA+HHB+ccfxAG7zuhwySRJksa2rgsgKH793xc4tuINwbcj4izg48A7gfMbvNZnM3PeEO59AbAzcExm/qE8dmFE7AecEhGXZ+YPhnA91bBxY3L6t27m2ruXP3nso6/bjxfvPbuDpZIkSRJ0WQAREdOAtwMPAT+sSp4PnAecRuMBxFDuvSfwKmBBRfDQ72LglPLeXRdADGcswXDHIdTK/80bHuB7v3/wyXP+4Zi9+avn7jrk55IkSVLrdVUAAbwEmETxJX6z8QaZuTwiFgJ7R8Rembmwxfd+Zbm/rkba7ym6PB0ZEVMyc4vuT6PRNYuW8akr7+L6ex/eIu3Q3Wdy6gCzGQ0n72D5K51w2G787ZFPH+RJJEmSNFK6bR2I/cr9fXXS+4/vVye92nMi4oqIWBwRayPi7oj4bEQ8dSj3zsyNwAMUAdkzG7x3R33jhvs54aIFdb/AX3/vw5xw0QK+ecMDLc3bSP5+z37KdOa95tlExCBPI0mSpJHSbQHETuX+kTrp/QsD7Njg9V4AfAvYB5gJ/APwBuCmiHhWu+4dETfW2spytN01i5ZxxmW3sHGQOaM2JvzTZTdzzaJN48yHk3co+QFuf+gxfn3P8sFPlCRJ0ojptgBicrmvN1XrunI/pYFrfQ04NDMvycxHM3NVZl5GMZPSLOCrbbx3R33qyrsa+gIPRSDw6SvvakneVuSXJElSZ3XbGIjV5X5CnfSty/2gYxAGGCPxHWAJcGBE7JeZt7Th3gfXOl6+hThosPzDsXBJ36Bdh6otuPdhTrjo1wBN5502aQJ9a9Y3lX/hkj7Xe5AkSRolui2AWFzut6uT3r9IwJJmb5CZGRH3UnRF2gfoDyDafu+RUN2lqFG/vKv5rkTDyQtFmQ0gJEmSRodu68LU/2V+9zrpc6rOa1atUbt17x0R44BdgSeA24d577ZauWZDp4swZN1YZkmSpF7VbQHEVcBa4NComponIrYH9gLuHmwK14jYtZx5aYtljcvr7lH+eWdFUv/6DofVuOQBFGMfrh7tU7hOndTcS6fXH7wLrz94l6bzfu7NBzWdv9kyS5IkqfW6KoDIzD7gIorVoF9RlTyX4s3BJ/sPRMT0cprWSyJifMW54ym6KB1d4zbHATsAN1PxJiMz76IIIg6NiH2r8pxU7j/JKDfQ2gwDOflFe3Dyi/YY/MQ6eY/df+em8zdbZkmSJLVeVwUQpQ8CtwEXRsQLImJyRLwWmAf8GPh8xbkvA44FTgQOrDjePw/Q5yLizRExKyK2iYjjgAsopmo9sXqxOuDdFGMhvh4R+0fElIg4GXgXcHFmXtHaR229vXacxqG7zxxSnuftPpO9dpw2rLzDvbckSZJGh64LIDJzBXA48N/A1ynWXzi33F6dmZUd5q8F7gFuAG6tuMYfgUMppnI9naKr0sPAx4BvAgdk5u9r3Pt+4LnAb4CflHneC5wGvL2Vz9lOpx61J+MaXJttXMB7j9qzJXlbkV+SJEmdFVv+yK5OiYgbDzrooINuvPHGtt/rGzfcP+iCbuMCPvq6/XnDIbu2LG8r8kuSJGl4Dj74YH7729/+tt7yAgNxdOoY9cZDnsYu203h01fexYIaazM8b/eZvPeoPWuOPxhO3lbklyRJUucYQIxhRzxjFkc8YxYLl/RxzaJlrFyzgamTtuKIZ8wadNzBcPK2Ir8kSZI6wwBCTw6QHum8rcgvSZKkkdV1g6glSZIkdY4BhCRJkqSGGUBIkiRJapgBhCRJkqSGGUBIkiRJapgBhCRJkqSGGUBIkiRJapgBhCRJkqSGGUBIkiRJapgBhCRJkqSGRWZ2ugwqRcTyyZMnz3zmM5/Z6aJIkiSph91+++2sXr364czcfqh5DSBGkYi4F5gO3NfhogzVPuX+jo6WovtYb82x3ppjvTXHemuO9dYc66051ltz5gCPZebuQ81oAKFhi4gbATLz4E6XpZtYb82x3ppjvTXHemuO9dYc66051tvIcwyEJEmSpIYZQEiSJElqmAGEJEmSpIYZQEiSJElqmAGEJEmSpIY5C5MkSZKkhvkGQpIkSVLDDCAkSZIkNcwAQpIkSVLDDCAkSZIkNcwAQpIkSVLDDCAkSZIkNcwAQgOKiPkRkQNsu9TIs1dEfCsilkXEqohYEBFv7ET5R0pEzIqIb5R1MneQc4dcPxHx8oj4eUT0RcQjEXFFRBzc0ofogEbrLSLuG6ANLhogX8/UWxReHRGXRsT9EbEuIh6NiF9ExAkD5BvT7a2ZerO9QUSMi4ijI+IzEfG7iHg4Ih6LiFsj4ryIeEqdfGO9vQ253mxvtZX/3WZE1F1vYKy3t04ygFAjFgN31tnWV54YEQcAvwF2AA4Ddga+D1waER8cwTKPmIg4DrgVeFkD5w65fiLiJOCHwO+B3YD9gHXAtRFxZAseoSOGUm+le6jdBu+uc/1eq7d/Br4LbA/8JTADeD7wCPDliLi4OoPtDWii3kpjvb3NBH5M8d/n6cDTgKcDnwTeC/wuqn5Asr0BTdRbaay3t81ExDTg/EHOsb11Uma6udXdgPnA3AbPHQfcBKwEZlelfQ94Ati308/U4vp5N/AgcGxZV1mvvpqpH+CpwGpgAeXCj+XxbSgCu/uBiZ2uh3bWW3n+fcCcIVy/5+oN+Ney7FOrjm9N8SUjgZfY3oZXb7a3J8s+q6yb59dI+1SZdrbtbXj1Znur+4znA9eV9ZU10m1vHd58A6FWeglwAHBFZi6tSruY4j/4U0e8VO11C/DszPx+A+c2Uz/vBiYBX8ry/+kAMnMV8A1gV+D1TZa9k4ZSb83oxXr7E3BJZq6sPJiZ64CflH++tCLJ9lYYar01oxfrbQXwYoovW9XuKvczKo7Z3gpDrbdm9GK9PSkijgBOAt4xwGm2tw4zgFArHVvur6uRdl3VOT0hM3+VmY80eHoz9dOTdTrEemtGz9VbZl6QmR+ok9xX7qPimO2NpuqtGb1Yb+sz8+rM3Fgj+bByf2XFMdsbTdVbM3qu3vpFxNbAF4HzMvMPA5xqe+swAwg14sUR8bNykNLqiLg9Iv49IrarOm+/cn9f9QUyczGwBtg5IrZvc3lHqyHVT0SMB55VL0/Fsf1qpPWid0bETRGxshz89uuIeHdEbPb/Y2O03vYq97+oOGZ7G1yteutne6sQEZMiYu+IOBd4I0U3nO9WnGJ7q6GBeutneyt8iOK76b8Ocp7trcMMINSIv6Dou7kbxSCl8ygGg/0mInaqOK//f9f7ZXlFud+xHYXsAkOtn+0o+mlnZq6ocf6jVef3uucDJ1MMht2H4kvf+cDl5T8O/cZUvUXETOAY4HfAjyqSbG8DGKDe+tneShHxcoq+43cAbwFOBD5SdZrtrUqD9dZvzLe3iHgW8I/AOzJz7SCn2946zABCg/kExWCwyzNzVWY+mpkXU8xssgdwQcW5k8v9+uqLlNaV+yntKeqoN9T6sT43OQl4WWZen5lrM/NPmfmPwHeAVwOnVJw71urtXIqBhidW9uvF9jaYevUGtrfNZOaPgPFsmk3oIuBHVW+TbW9VGqw3sL1Rvmn5L2B+Zv6ygSy2tw4zgNCAMvP3mflQjaQvUvzj+5qI6B8QtrrcT6hzua3L/eMtLGI3GWr9WJ+lzLyqHPRa7cJyf2LFsTFTbxHxFmAu8JYa/YVtb3UMUm+2txoyc2Nm3pOZ5wEfAI6meDPdz/ZWQwP1ZnsrvIeil0O98UrVbG8dZgChppSzFiyhaEN7locXl/vqsRH9ti33S9pYtNFsqPXzCMWvIhER29Y4f0bV+WNR/xzp+1QcGxP1FhFHU/xid3JmXlbjFNtbDQ3U20DGbHurclG5f3NEbFP+b9vb4GrV20DGRHuLiF2Bc4BT6nQvqsX21mEGEBqO6plLbin3u29xYjFWYhLwUGYub3fBRqkh1U9mPgHcVi8PMKfqumPRFrPnjIV6i4iXApcD7ym7FNZie6vSYL0NeInqA2Oh3qpl5uPAnynq4+nlYdvbIOrU20DGSns7CpgGXBZVK3H3n1Bx7OrykO2twwwgVFdEHB4Rd9VJmwrMBjYCi8rDPyj3h9XI8vyqc8aiZupnzNdpRJweEZfUSe7/R/jOquM9W28RcRTFl+D3Vn4JjohnR8QbK061vVVotN5sb4WI+FBE1HxDU061ObP887Fyb3tj6PVme4PMnJ+ZUWurOKf/2JHlIdtbp+UoWM3ObXRuwJEU4xwOqZF2epn23Ypj44CbGXhlyP07/VxtrK/5DL4S9ZDqh2Jhm3orZz4EPABM6vSzt7ne5lG8rp5WI+2KMu/7xkK9USyetBJ4e420ucDVtrdh15vtbVM9/BmYUafOErjV9jbserO9DVyfA61EPebbW0c/m04XwG30bhTTtyZFP8xjKfoUbgu8jWKg0R+BXaryHEixONPVFL+eTAfOLK9zZqefqc31NZ8Bvgg3Wz8Uq3Em8GmKX6+eClxG0Z/zqE4/d7vrDTirTP8p8FyK2TSeCvxHefxHwIRerzeK1W0fL/+hu7TGtoCKL8K2t+bqzfa2RT38CnghRReTnSlW832M4ovbEba34dWb7W3Q+qwZQNjeOr91vABuo3ej6H95JMVMEDdTzKu8mqIf4UeBmXXy7QP8N7C8/If7BuCvO/08baqjOf3/B1dju69V9QO8Avhl+Y/PoxSvWZ/b6ecfiXor/0F9Y/l/8gvLNvgYxcqh7wHGj4V6Y1OgNdB2te1tePVme6tZD3eUz7S6rJMLgD3q5Bvr7W1I9WZ7q/lccwf4b/VI29vo2KKsTEmSJEkalIOoJUmSJDXMAEKSJElSwwwgJEmSJDXMAEKSJElSwwwgJEmSJDXMAEKSJEkkASpXAAAJtklEQVRSwwwgJEmSJDXMAEKSJElSwwwgJEmSJDXMAEKSJElSwwwgJEmSJDXMAEKS6oiI+yIih7DN6XSZBxIRcyNi3gDpF0TE0oh45ggWa0ARsWEI9X/1CJVpXuV9R+KeNcpwZFmOOXXSj4+Ivog4fmRLJmksMICQpDoyc05mRsXfUWsDdu9gMYdiLnDWAOlzgJnAdiNRmEZk5lZsqt8/DvAZnD2CZZpX3vPnI3XPGo6k+Czn1El/KjC13EtSS23V6QJIkkaN1wDbZebSThdEw5OZH4uIr2bmnzpdFkm9xzcQkjR8fwSmlfuulZnruzh4+DfgFZ0uxGhi8CCpXQwgJKlJETGn7AO/W2auzMys6h9/X9X5KyvS5lYcf1NVX/49I+LfIuJPEbEmIn4XES+tU4YpEXFmRNxenrskIn4dER+MiKeV58wty/kX5d+V95rb/xy1ylZxn+0j4j8j4t6IWFve59KIeFbVeZ+vfP6I2Kk875GIWBURP4yIPYZZ9ZX3mxsR92XmusxcXR6bF1uOjziyTKt+1qsrnu/9EfHziFhcPuOiiDg3IqY2WJbqax9ZkfbZgcZqRMRry3paVH6OyyLi8og4qNY92NQV7WcV151fnnNf9bGqa2wVEX8fETdFxOqIWBERV0XEK6vOa6pdRsTkiDgjIm4t2/yDEXFlRPxdRMxspC4ljW4GEJLUQhX947d4G5GZU4G31jh+aZnnkvLQJ4B7gGcDBwMTgO9GxK6V+SJiCvAz4P3AhyjGLjwH+AlwDvDp8vrzK/vsV40fmJ+Z95XpW5StvM/OwPXAG4C3AdMp+uA/Bbg+Il5U8Szvqnj+rctn+gLwNOD1wBHAd+pWYAtk5jxgz/LPBeVzXl2m9T/rtcA7M/PI8rwXA+cBPwD2BWYB76F45p9ExPgG7tt/7S3GY2TmKZXjaWr4SnnPvwRmUNTTWuCaiDh4gHu8uOKznFueM4c643LK57gcOBf4HLADsDdwG/D9iHh/xb2aapfAV4EzgH8EdqRok7+gaI+vGaAOJHUJAwhJalD1r9rAvW261T2Z+V+Z+Whm3gp8BJgMHFd13r8AhwL/kJn/k5mrM/OhzDwT+H4Ly3M+sAdwUmZelZlrM/N24LVAAl+LiIk18u0MfCEzf5aZfZn5Q4ovl/tGxHOaKMduNT6DL9U6MTMXAb8EnlfjLclewIHANyoOPwpcnJkfy8xlZXn/FzgVOAz4P02UdyhuBk7MzFszc01m3gkcDzwGzGvhfU4BjgU+nplfLN+cLc7MU4DrgHMj4oA6eQdtlxExg6Jd/Dgzv5+ZqzJzaWaeDfyqhc8hqYMMICSpQSM4+1L1L/S3l/v+X9WJiK2Ad1B8gf8GW/oUxZuIYSnfPvwlsLz6epnZf+yp5TnVNgLfqzq2xbMMwRazMFHnrUmpP7g4qer4ScBlmbmi/0Bm/jQz317jGreU+yOaKG/DMvPwzHyw6th64M4W3/td5f7rNdIupfhe8M46eQdtlxSfeQCHRcRuVecfB/xP40WVNFoZQEjS6PNg1d8ry/2UimN7UwzcfigzH6u+QGb+JDM/14KyHEzxhfDOzKy15sEd5f6QGmnLyi/BlWo9S7t8C1gFnFAGXP1deE6gxpuLiHhVRPy07OO/sXzDcXeZ3NapbSNi94j4QkTcWY5L6H/D8sJW3TsipgH7lH/eUeOUgT5LaKBdlm3xIoqg8o6I+EZEHBcRU8o3EX3NlV7SaGIAIUlN6u+Pnpn3tfjSq6tvVe4r+9DPKPerWnzvatsOcp/+4zNqpFU/B9R+lqaVYzjm1ElbSRFEzAZeVR4+BlgPXFV5bkR8kOJtyVrgaGBi1VumlpS3ligW7ruJopvU+4EdK96wtHKtienlfn2NwA4G/iyhsXYJxZuxt1K8oXgD8N/Ag+UA7K2HVmRJo5EBhCS1R70Vilv1y/uj5X6bFl2v2fv0H3+kzeVoVnU3ppOA+ZVvU8ovtR+k6H5zfGbeVucLdqNqfvbloPdaTqP4cn9OZl5R641Si/R/lhMiYkKN9JZ8llmYn5kHUbwp+whF0HYGxXgaSV3OAEKS2mM1tb90t2pl4DsoBtjuHBHbVidGxKER8bdVh+sFNQP5DcUX670jotav8M8s99c3ce2WiYgDK2cQ6peZvwAWAa+IiGdTvIm4pOq0WRSf1bLMrP7yPLmJ4vT/Ul/9+df77OeU+7tqpNW7/5A/y8xcRTHbEmz63CoN+7OMYlrhl1fcc2FmnkXRLWoDxUxckrqcAYQktcddwKyI2L7qeEtm88nMJ4AvUnQfeUONUz4OVM/R/whAREwq9++LiAEHtWbmEuDbwPbAyyrTymc7GvgTWw6WHmkHAH9XJ20+sBVFV5prM7N69qxlFF/6d4iInarSXtBEWfoDgb2rjr+2zvn3l/v9Kw9GxHbAs7Y8Hdj0lqD/s3xhRPwhIqbXOb/fBeX+r2ukvYkiWLxwkGsMZDbwvXK8xZPKbn6rqN2tTVKXMYCQpPb4v+X+E1EspvaUiPgM8P9aeI8PU/xafF45UHVyROxS3mc/im45lX5T7l8aEbOAvwEaGdT6HorBxBdFxEsiYuuI2Ae4rEx/c2auHfbT1FC+Xen/UjwuImbU2hi4a9glFF+M96HG4OnMXEexJkIAl0bEsyJim4h4DcV6GkP1Y+DPwKnlm6BpEfE66g9OPh9YB5wREa+LiKkRsTfF7Fr1uo71f5YvjohtgLnA1Aa6P50PfBd4f0S8o3zOHSPisxTT1X4gM29u9EHr2Ipiat9nR8TEiHhqRPwnxXiaTw7z2pJGg8x0c3Nzc6uxAfdRdBWp3o5sMP/7ymuso+g68maKL3qV15pFsShb9T2uLq9x9UD3p/ji/GGKAatrKGbK+RbwzBrlmUYR2CwDVgBXUCwGN6fOc86pyDsT+A+KhcTWAUsppv18VtU95tW4zrwybYt7NFCHG+qUrdZ23wDX+V+KLl9T6qSPpwiUbgEep/iF/3sUXW42q/s6z3h11fWeS7HuwRqKYOJ8imCgMs/pVef/qPxs1gC/L8vz84rz51fd40zggbK8vwGOGKDdzq161lMpBm6vLuvlZ8CxVdc/st5zUqddUgQPf0UxXevd5fWXls/x+k7/N+3m5taaLTKb6RIrSZIkaSyyC5MkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhhlASJIkSWqYAYQkSZKkhv1/iA6uaAsjH+wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 276,
       "width": 392
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from pymoo.performance_indicator.hv import Hypervolume\n",
    "\n",
    "# create the performance indicator object with reference point (4,4)\n",
    "metric = Hypervolume(ref_point=np.array([1.0, 1.0]))\n",
    "\n",
    "# collect the population in each generation\n",
    "pop_each_gen = [a.pop for a in res.history]\n",
    "\n",
    "# receive the population in each generation\n",
    "obj_and_feasible_each_gen = [pop[pop.get(\"feasible\")[:,0]].get(\"F\") for pop in pop_each_gen]\n",
    "\n",
    "# calculate for each generation the HV metric\n",
    "hv = [metric.calc(f) for f in obj_and_feasible_each_gen]\n",
    "\n",
    "# function evaluations at each snapshot\n",
    "n_evals = np.array([a.evaluator.n_eval for a in res.history])\n",
    "\n",
    "# visualze the convergence curve \n",
    "plt.plot(n_evals, hv, '-o')\n",
    "plt.title(\"Convergence\")\n",
    "plt.xlabel(\"Function Evaluations\")\n",
    "plt.ylabel(\"Hypervolume\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We hope you have enjoyed the getting started guide. For more topics we refer to each section covered by on the [landing page](https://pymoo.org). If you have any question or concern do not hesitate to [contact us](contact.rst)."
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Raw Cell Format",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
